Annals of Nuclear Energy 57 (2013) 179–184

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Annals of Nuclear Energy

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Analysis of surface contributions to external doses in a radioactivelycontaminated urban environment designed by the EMRAS-2 Urban AreasWorking Group

0306-4549/$ - see front matter Crown Copyright � 2013 Published by Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.anucene.2013.01.040

⇑ Corresponding author. Tel.: +82 2 868 2344; fax: +82 2 868 2370.E-mail address: wthwang@kaeri.re.kr (W.T. Hwang).

Won Tae Hwang ⇑, Hae Sun Jeong, Hyo Joon Jeong, Eun Han Kim, Moon Hee Han, In Gyu KimKorea Atomic Energy Research Institute, 1045 Daedeok-daero, Yuseong-gu, Daejeon 305-353, Republic of Korea

a r t i c l e i n f o

Article history:Received 17 October 2012Received in revised form 22 January 2013Accepted 23 January 2013Available online 5 March 2013

Keywords:EMRAS-2 Urban Areas Working GroupHypothetical scenariosUrban environmentRadioactive contaminationExternal dose

a b s t r a c t

The EMRAS-2 Urban Areas Working Group, which is supported by the IAEA, has designed a variety of acci-dental scenarios to test and improve the capabilities of the models used for an evaluation of radioactivecontamination in an urban environment. A variety of models including a Korean model, METRO-K, areused for predictive results on the hypothetical scenarios. This paper describes the predictive results ofMETRO-K for the hypothetical scenarios designed in the Working Group. The external dose resulting fromthe air contamination of Co-60 was evaluated, and its contribution was analyzed with time as a functionof the location of a receptor and precipitation conditions at the time of the contamination event. As aresult, the external doses showed a distinctive difference with the locations to be evaluated and the pre-cipitation conditions. Moreover, the contribution of contaminated surfaces for external doses wasstrongly dependent on the locations to be evaluated and the precipitation conditions. These results willprovide essential information to assist the decision-making of appropriate countermeasures in an emer-gency situation of a radioactively contaminated urban environment.

Crown Copyright � 2013 Published by Elsevier Ltd. All rights reserved.

1. Introduction

Radioactive contamination in an urban environment may becaused by an accidental release of radioactive materials fromnuclear facilities or a deliberate explosion of radiological dispersaldevices. Thus far, studies on radionuclide behavior in the environ-ment have been mainly focused on soil or agricultural fields be-cause nuclear facilities are situated in a rural environment inmany cases. Interest in radionuclide behavior in an urban environ-ment, which is covered with artificial surfaces such as asphalt orconcrete, has been increasing since the Chernobyl nuclear accidentin 1986 and the Goiania radioisotope accident in 1987. Moreover,the September 11 attacks in 2001 provided an additional motiva-tion to recognize the importance of radioactive contamination inan urban environment.

An international program EMRAS (Environmental Modelling forRAdiation Safety) was launched by the IAEA (International AtomicEnergy Agency) to test and improve the capabilities of models usedfor an environmental impact assessment in 2003. The EMRASUrban Remediation Working Group was organized to test andimprove the capabilities of the models for predicting the exposuredose owing to the contamination of urban areas (IAEA, 2012;

Thiessen et al., 2008; 2009a, b). EMRAS-2 (Environmental Model-ling for RAdiation Safety, Phase 2), the follow-up program of theprevious EMRAS, was successively launched in early 2009. The EM-RAS-2 Urban Areas Working Group was organized for the purposeof a further understanding and harmonization of radionuclidebehavior in urban environments. The Working Group designed avariety of hypothetical scenarios for an intercomparison of themodel prediction. A Korean model, METRO-K (Model for Evaluatingthe Transient Behavior of RadiOactive Materials in the Korean Ur-ban Environment) (Hwang et al., 2005a, b; 2007), joined theintercomparison.

In this paper, a modeling approach for the application ofMETRO-K to the hypothetical scenarios was described. The exter-nal doses resulting from air contamination were evaluated forhypothetical scenarios using METRO-K, and their contributionswere analyzed with time as a function of the location of a receptorand the precipitation condition at the time of the contaminationevent.

2. Materials and methods

2.1. General description of METRO-K

Fig. 1 shows a schematic diagram of METRO-K to predict theexposure dose in an urban environment with a starting point of

Fig. 1. Schematic diagram of METRO-K to evaluate the exposure dose at specifiedlocations (CAP represents the minimum precipitation amount that occurs a run-off,and is an abbreviation of the Critical Amount of Precipitation).

180 W.T. Hwang et al. / Annals of Nuclear Energy 57 (2013) 179–184

radionuclide concentration in air. In the case of an accidentalrelease from a nuclear facility or an explosion of a radiological dis-persion device, radioactive materials released into the atmospherewill be deposited onto the surfaces through not only dry processesby atmospheric turbulence and gravitation, but also wet processesby precipitation. The surface contamination through dry and wetprocesses can be predicted from empirical parameters, called thedeposition velocity and washout ratio, respectively. The radionuc-lides deposited through dry processes are classified into mobileand fixed fractions. The mobile radionuclides can be easily re-moved from the surfaces by external environmental factors suchas wind and precipitation. On the other hand, fixed radionuclidescannot be easily removed. A certain fraction of the mobile radio-nuclides accumulated in the previous day will be fixed owing tomoisture for the night of that day. Thus, the portion of fixed radio-nuclides will be increased from day to day with a certain fraction.In the case of wet processes, a terminology, i.e., a CAP (CriticalAmount of Precipitation), is used to quantify the run-off process,which is defined as the minimum precipitation at which arun-off occurs. If there is a slight precipitation below CAP duringa release of radioactive materials, both dry and wet processes will

Fig. 2. A close-up photograph of an urba

occur. All of the deposited radionuclides will be fixed. If there is aheavy precipitation exceeding CAP during a release of radioactivematerials, radionuclides will be deposited through wet processes.Some radionuclides will be fixed, while others will be removed to-gether with the run-off water. A certain fraction of the radionuc-lides in run-off water will be retained on the surfaces. As shownfrom the Chernobyl experience, radioactive materials may be re-leased for several days in the case of a severe accident. The totaldepositions on different surfaces are calculated step by step fromthe air concentration and precipitation on a daily basis. Whilebeing deposited, radionuclide concentrations on the surfaces arecorrected through radioactive decay, but environmental removalis not considered. After the deposition processes are completed,radionuclide concentration on the surfaces will be affected byweathering processes including wind, pedestrians, and traffic aswell as a migration into soil. The absorbed dose is calculated as afunction of the location of a receptor using predetermined airkerma. The air kerma was originally derived by Jacob et al. (Jacobet al., 1988), but it was rearranged and modified for applicationto the Korean environment. The total exposure dose for a specifiedlocation is evaluated by summing the exposure doses resultingfrom each contaminated surface. METRO-K is a dynamic modelthat is able to predict the total exposure dose with time followinga contamination event. METRO-K considers three radionuclides(Cs, Ru, and I) and three types of iodine (elemental, organic, andparticulate forms). Many of the parameter values used inMETRO-K are dependent on the radionuclides and type of surfaceson which radionuclides are deposited. A detailed descriptionincluding the parameter values is found in references (Hwanget al., 2005a, b; 2007).

2.2. Radioactive contamination scenarios

Fig. 2 shows an urban region selected to test models in theEMRAS-2 Urban Areas Working Group. A variety of characteristicdata such as the size and building materials, and the width ofroads, were provided to the modelers. A variety of scenarios weredesigned in the Working Group, but only the scenarios related tothe purposes of this paper were described. The scenario beginswith the concentration of radionuclide in air, due to an unspecifiedcontamination event. It is assumed that the initial air concentra-

n region for hypothetical scenarios.

W.T. Hwang et al. / Annals of Nuclear Energy 57 (2013) 179–184 181

tion of Co-60 is 1 MBq day m�3 with the same concentration overthe entire space. Two different precipitation conditions at the timeof a contamination event are assumed: one is a dry condition with-out precipitation, and the other is a wet condition with a precipita-tion of 20 mm. Building 1 in Fig. 2 is a 24-story business building66 m in height and 903 m2 in cross-sectional area with a roundshape. The roadway running north–south has 16 lanes. Each laneis 3.5 m wide. The surface is covered with asphalt. The sidewalkis 10 m wide and is covered with ceramic tiles or cement bricks.The avenues are lined with street trees, which are deciduous withbroad leaves. Street trees 7 m in height are planted at 8 m intervals.The endpoints of interest are the external dose in terms of the ab-sorbed dose in air at four different specified locations (groundfloor, 10th floor, top floor, and outside – sidewalk in front of the

(a) For different

(b) For differe

Fig. 3. The approach used for a modification of the kerma values fo

building) of Building 1 and the contribution of contaminatedsurfaces for an external dose with time following the contamina-tion event.

2.3. Application of METRO-K to the scenarios

The prediction of external doses in a radioactively contaminatedurban environment may be a difficult task because of the geomet-rical complexity of the surrounding environment and the diversityof the surfaces composing it. For this reason, METRO-K uses prede-termined kerma values, which represent the absorbed dose in airper unit of deposition and photon, for specified environments.Among them, the most similar environment was selected, andcompared with the hypothetical environment to be evaluated.

building heights

nt road widths

r application of a METRO-K environment to a hypothetical one.

Fig. 4. A simplified geometry used to simulate hypothetical scenarios.

0 200 400 600 800 1000 1200 1400 1600 180010-5

10-4

10-3

10-2

10-1

Exte

rnal

dos

e ra

te (m

Gy/

hr)

Time following an event (days)

Ground floor 10th floor Top floor Outside

Fig. 5. Predicted external dose rates for specified locations over time following acontamination event, assuming that there is no precipitation.

182 W.T. Hwang et al. / Annals of Nuclear Energy 57 (2013) 179–184

The kerma values applied in METRO-K were then rearranged andmodified to describe a hypothetical environment. Fig. 3 shows anapproach for the modification of kerma values for an environmentwith different building heights and different road widths. For acontamination of the roofs, it is assumed that the kerma valueson the top floor of a 24 story building are the same as those onthe top floor of a 10 story building, symbolized as K1, as shownin Fig. 3a. For a contamination of the trees, it is assumed that thekerma values on the ground floor of a 10 story building are thesame as those on the ground floor of a 24 story building, symbol-ized as KG. On the other hand, for a consideration of different sizedcontamination areas, the kerma values are modified as well,assuming that they are inversely squarely proportional to the dis-tance from the location to be evaluated with several partitions ofthe contamination area of the equivalent size to be considered inMETRO-K, as shown in Fig. 3b.

The kerma values are provided for three different photon ener-gies (0.3 MeV, 0.662 MeV, and 3 MeV) as a function of the locationsto be evaluated. The kerma values for the energies and locationsnot specified in METRO-K were derived through a logarithmicinterpolation. These values are representatives for a specified loca-tion, and are not exact values of a point in space.

A radionuclide of interest, Co-60, is not considered in METRO-K.Thus, a variety of parameter values describing the environmentalbehavior are based on those of Cs-137 except for the inherentphysical characteristics of a radionuclide. This is because theparameter values of Cs-137 have been relatively well-establishedfrom the abundant literature. In addition, the parameter valuesdescribing the environmental removal following a deposition werereplaced with those derived from Anderson’s recent study(Andersson and Roed, 2006), which may be a better descriptionfor long-term radionuclide behavior in an urban environment.The physical characteristics of radionuclide in METRO-K are mod-ified for Co-60, instead of Cs-137. Co-60 is a beta emitter with ahalf-life of 5.3 years, and is converted into a stable nuclide Ni-60.Photon energies emitted from the radioactive decay of Co-60 are0.69382 MeV, 1.1732 MeV, and 1.3325 MeV with yields of0.0163%, 100% and 100%, respectively (Shleien, 1992).

0 200 400 600 800 1000 1200 1400 1600 1800

10-2

10-1

100

101

102

Exte

rnal

dos

e ra

te (m

Gy/

hr)

Time following an event (days)

Ground floor 10th floor Top floor Outside

Fig. 6. Predicted external dose rates for a specified location over time following acontamination event, assuming that there is heavy precipitation of 20 mm.

3. Results and discussions

Using METRO-K, the external doses for the specified locationsand their contributions were evaluated and analyzed for a hypo-thetical scenario designed in the EMRAS-2 Urban Areas WorkingGroup. The endpoints were carried out over time as a function ofthe location to be evaluated and the precipitation conditions atthe time of the contamination event. The external dose is ex-pressed in terms of the absorbed dose in air. Fig. 4 shows a simpli-fied diagram for the region of interest to simulate a hypotheticalscenario using METRO-K.

Fig. 5 shows the external dose rates at specified locations of thebuilding over time following the contamination event, assumingthat there is no precipitation (dry condition). The figure shows agreat difference between the inside and outside of the building be-cause of its shielding effect. Moreover, it shows a great differenceamong the inside locations of the building. The external dose ratesare the highest outside of the building, while they are the loweston the 10th floor. Just after an event, the external dose rates onthe ground and top floors are similar, however, they show a dis-tinct difference over time following a contamination event. Thisis due to the different behavior of the radionuclides on eachsurface.

A nuclear event may take place on rainy days. Fig. 6 shows theexternal dose rates at specified locations of the building over timefollowing a contamination event, assuming that there is 20 mm

(wet condition) of precipitation. Compared with a dry condition(see Fig. 5), the external dose rates are higher because of a greatercontamination density of surfaces in the case of wet conditions.Differently from dry conditions, the external dose rates on the

Ground F.10th F. Top F. Outside Ground F.10th F. Top F. Outside0

10

20

30

40

50

60

70

80

90

100

Wet conditionLocations of a receptor

Perc

ent c

ontri

butio

n fo

r ext

erna

l dos

e ra

te

Dry condition

roof outer wall road street tree

Fig. 7. Percent of contribution of contaminated surfaces for external dose rates ofspecified locations just after a contamination event, under different precipitationamounts.

Year 0 Year 1 Year 5 Year 0 Year 1 Year 50

10

20

30

40

50

60

70

80

90

100

Wet conditionTime following an event

Perc

ent c

ontri

butio

n fo

r ext

erna

l dos

e ra

te

Dry condition

outer wall road street tree

Fig. 8. Percent of contribution of contaminated surfaces for external dose rates onthe ground floor over time following the contamination event, under differentprecipitation conditions.

Year 0 Year 1 Year 5 Year 0 Year 1 Year 50

10

20

30

40

50

60

70

80

90

100

Wet conditionDry condition

Perc

ent c

ontri

butio

n fo

r ext

erna

l dos

e ra

te

Time following an event

outer wall road street tree

Fig. 9. Percent of contribution of contaminated surfaces for external dose rates onthe outside over time following the contamination event, under different precip-itation conditions.

W.T. Hwang et al. / Annals of Nuclear Energy 57 (2013) 179–184 183

top floor are not as high as those on the ground floor just after thecontamination event.

Fig. 7 shows the percent of contribution of contaminated sur-faces for the external dose rates at specified locations just afterthe contamination event, under different precipitation conditions.For the ground floor, the street trees and roads including the side-walks are the greatest contributors under dry and wet condition,respectively. The outer walls and roofs are dominant contributorsfor the 10th and top floors, respectively, in the case of both dryand wet conditions. For the outside, under a dry condition, thestreet trees are the greatest with a 51% contribution, followed byroads with a 47% contribution. Under wet conditions, the roadsare dominant with a 92% contribution. Thus, it can be concludedthat the contribution of contaminated surfaces is strongly depen-dent on not only the locations to be evaluated, but also precipita-tion conditions.

Fig. 8 shows the percent of contribution of contaminated sur-faces for an external dose on the ground floor until the 5th year fol-lowing the event, under different precipitation conditions. The

contribution of street trees is decreased gradually over time owingto a relatively short environmental half-life of 100 days, while thecontribution of roads and outer walls is increased with time.

Fig. 9 shows the percent of contribution of contaminated sur-faces for the external dose rate on the outside until the 5th yearfollowing the event, under different precipitation conditions. Thecontribution of street trees is decreased with time, while the con-tribution of roads is increased, owing to the different environmen-tal half-lives of the contaminated surfaces.

For the 10th floor, there is only one major contributing surface(outer walls) over the entire period to be evaluated, with no differ-ence between the dry and wet conditions at the time of the con-tamination event. For the top floor, the roof essentiallycontributes all of the dose rate (outer walls just a tiny fraction)over the entire period to be evaluated, with no significant differ-ence between dry and wet conditions at the time of the contamina-tion event. This is due to a relatively short distance from thesurface and the location to be evaluated.

4. Conclusions

Using METRO-K, the external doses were predicted over timefollowing an event as a function of the location to be evaluatedand the precipitation condition at the time of the contaminationevent, for a hypothetical scenario designed in the EMRAS-2 UrbanAreas Working Group. Also, the contributions of the contaminatedsurfaces for the external dose were analyzed. As a result, the exter-nal dose showed a great difference with not only the locations tobe evaluated, but also the precipitation. Moreover, the contributionof contaminated surfaces for external doses was strongly depen-dent on the locations to be evaluated and the precipitation condi-tions. Therefore, it would be important to collect information aboutthe weather conditions at the time and place of an actual contam-ination event. The model results might be used to assist in deci-sion-making regarding which countermeasure can be the mostuseful, or when the countermeasure can be most usefully applied.For example, removal or defoliation of trees just after a contamina-tion may be a cost effective countermeasure, if a contaminationevent occurs during the time of year that the trees have leaves. Acomparison of the predictive results among the models is in pro-gress at the Working Group, and comprehensive results will bepublished as a technical report of the IAEA in the near future.

184 W.T. Hwang et al. / Annals of Nuclear Energy 57 (2013) 179–184

Acknowledgements

This work was supported by Nuclear R&D Programs of Ministryof Education, Science and Technology of Korea, and Nuclear Safetyand Security Commission (Grant Nos. 2012011939 and2012028803).

References

Andersson, K.G., Roed, J., 2006. Estimation of doses received in a dry contaminatedresidential area in the Bryansk region, Russia, since the Chernobyl accident.Journal of Environmental Radioactivity 85, 228–240.

Hwang, W.R., Kim, E.H., Jeong, H.J., Suh, K.S., Han, M.H., 2005a. A model forevaluating the radioactive contamination in the urban environment. Journal ofRadiation Protection 30 (3), 99–105 (in Korean).

Hwang, W.T., Kim, E.H., Jeong, H.J., Suh, K.S., Han, M.H., 2005b. A model forradiological assessment due to an urban contamination following an accidentalrelease into the environment. In: Proceedings from the Second InternationalConference on Radioactivity in the Environment, Nice (France), 2–6 October.

Hwang, W.T., Kim, E.H., Jeong, H.J., Suh, K.S., Han, M.H., 2007. A model forradiological dose assessment in an urban environment. Journal of RadiationProtection 31 (1), 1–8 (in Korean).

International Atomic Energy Agency (IAEA), 2012. Environmental Modelling ofRemediation of Urban Contamination Areas. Report of the Urban RemediationWorking Group of the EMRAS Theme 2. Environmental Modelling for RadiationSafety (EMRAS) Programme. IAEA-TECDOC-1678 (Companion CD).

Jacob, P., Meckbach, R., Parezke, H.G., 1988. Gamma exposures to radionuclidesdeposited in urban environments. Part I: kerma rates from contaminatedsurfaces. Radiation Protection Dosimetry 21 (3), 167–179.

Shleien B., 1992. The Health Physics and Radiological Health Handbook. Scinta, Inc.2412 Homestead Drive, Silver Spring Md. 20902.

Thiessen, K.M., Batandjieva, B., Andersson, K.G., Arkhipov, A., Charnock, T.W., Gallay,F., Gaschak, S., Golikov, V., Hwang, W.T., Kaiser, J.C., Kamboj, S., Steiner, M.,Tomas, J., Trifunovic, D., Yu, C., Zelmer, R.L., Zlobenko, B., 2008. Improvement ofmodelling capabilities for assessing urban contamination: the EMRAS UrbanRemediation Working Group. Applied Radiation and Isotopes 66, 1741–1744.

Thiessen, K.M., Arkhipov, A., Batandjieva, B., Charnock, T.W., Gaschak, S., Golikov, V.,Hwang, W.T., Tomas, J., Zlobenko, B., 2009a. Modelling of a large-scale urbancontamination situation and remediation alternatives. Journal of EnvironmentalRadioactivity 100, 413–421.

Thiessen, K.M., Andersson, K.G., Batandjieva, B., Cheng, J.-J., Hwang, W.T., Kaiser, J.C.,Kamboj, S., Steiner, M., Tomas, J., Trifunovic, D., Yu, C., 2009b. Modelling thelong-term consequences of a hypothetical dispersal of radioactivity in an urbanarea including remediation alternatives. Journal of Environmental Radioactivity100, 445–455.